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NEW QUESTION 27
A solutions architect is formulating a strategy for a startup that needs to transfer 50 TB of on- premises data to Amazon S3. The startup has a slow network transfer speed between its data center and AWS which causes a bottleneck for data migration.
Which of the following should the solutions architect implement?

A. Request an Import Job to Amazon S3 using a Snowball device in the AWS Snowball Console.B. Deploy an AWS Migration Hub Discovery agent in the on-premises data center.C. Enable Amazon S3 Transfer Acceleration on the target S3 bucket.D. Integrate AWS Storage Gateway File Gateway with the on-premises data center.

Answer: A

Explanation:
AWS Snowball uses secure, rugged devices so you can bring AWS computing and storage capabilities to your edge environments, and transfer data into and out of AWS. The service delivers you Snowball Edge devices with storage and optional Amazon EC2 and AWS IOT Greengrass compute in shippable, hardened, secure cases. With AWS Snowball, you bring cloud capabilities for machine learning, data analytics, processing, and storage to your edge for migrations, short-term data collection, or even long- term deployments. AWS Snowball devices work with or without the internet, do not require a dedicated IT operator, and are designed to be used in remote environments.
Hence, the correct answer is: Request an Import Job to Amazon S3 using a Snowball device in the AWS Snowball Console.
The option that says: Deploy an AWS Migration Hub Discovery agent in the on-premises data center is incorrect. The AWS Migration Hub service is just a central service that provides a single location to track the progress of application migrations across multiple AWS and partner solutions.
The option that says: Enable Amazon S3 Transfer Acceleration on the target S3 bucket is incorrect because this S3 feature is not suitable for large-scale data migration. Enabling this feature won't always guarantee faster data transfer as it's only beneficial for long-distance transfer to and from your Amazon S3 buckets.
The option that says: Integrate AWS Storage Gateway File Gateway with the on-premises data center is incorrect because this service is mostly used for building hybrid cloud solutions where you still need on- premises access to unlimited cloud storage. Based on the scenario, this service is not the best option because you would still rely on the existing low bandwidth internet connection. References:
https://aws.amazon.com/snowball
https://aws.amazon.com/blogs/storage/making-it-even-simpler-to-create-and-manage-your-aws-snow-fa mily-jobs/ Check out this AWS Snowball Cheat Sheet:
https://tutorialsdojo.com/aws-snowball/
AWS Snow Family Overview:
https://www.youtube.com/watch?v=9Ar-51Ip53Q

 

NEW QUESTION 28
A company has a hybrid cloud architecture that connects their on-premises data center and cloud infrastructure in AWS. They require a durable storage backup for their corporate documents stored on- premises and a local cache that provides low latency access to their recently accessed data to reduce data egress charges. The documents must be stored to and retrieved from AWS via the Server Message Block (SMB) protocol. These files must immediately be accessible within minutes for six months and archived for another decade to meet the data compliance.
Which of the following is the best and most cost-effective approach to implement in this scenario?

A. Establish a Direct Connect connection to integrate your on-premises network to your VPC. Upload the documents on Amazon EBS Volumes and use a lifecycle policy to automatically move the EBS snapshots to an S3 bucket, and then later to Glacier for archival.B. Launch a new file gateway that connects to your on-premises data center using AWS Storage Gateway. Upload the documents to the file gateway and set up a lifecycle policy to move the data into Glacier for data archival.C. Use AWS Snowmobile to migrate all of the files from the on-premises network. Upload the documents to an S3 bucket and set up a lifecycle policy to move the data into Glacier for archival.D. Launch a new tape gateway that connects to your on-premises data center using AWS Storage Gateway. Upload the documents to the tape gateway and set up a lifecycle policy to move the data into Glacier for archival.

Answer: B

Explanation:
A file gateway supports a file interface into Amazon Simple Storage Service (Amazon S3) and combines a service and a virtual software appliance. By using this combination, you can store and retrieve objects in Amazon S3 using industry-standard file protocols such as Network File System (NFS) and Server Message Block (SMB). The software appliance, or gateway, is deployed into your on-premises environment as a virtual machine (VM) running on VMware ESXi, Microsoft Hyper-V, or Linux Kernel- based Virtual Machine (KVM) hypervisor.

The gateway provides access to objects in S3 as files or file share mount points. With a file gateway, you can do the following:
- You can store and retrieve files directly using the NFS version 3 or 4.1 protocol.
- You can store and retrieve files directly using the SMB file system version, 2 and 3 protocol.
- You can access your data directly in Amazon S3 from any AWS Cloud application or service.
- You can manage your Amazon S3 data using lifecycle policies, cross-region replication, and versioning.
You can think of a file gateway as a file system mount on S3.
AWS Storage Gateway supports the Amazon S3 Standard, Amazon S3 Standard-Infrequent Access, Amazon S3 One Zone-Infrequent Access and Amazon Glacier storage classes. When you create or update a file share, you have the option to select a storage class for your objects. You can either choose the Amazon S3 Standard or any of the infrequent access storage classes such as S3 Standard IA or S3 One Zone IA. Objects stored in any of these storage classes can be transitioned to Amazon Glacier using a Lifecycle Policy.
Although you can write objects directly from a file share to the S3-Standard-IA or S3-One Zone-IA storage class, it is recommended that you use a Lifecycle Policy to transition your objects rather than write directly from the file share, especially if you're expecting to update or delete the object within 30 days of archiving it.
Therefore, the correct answer is: Launch a new file gateway that connects to your on-premises data center using AWS Storage Gateway. Upload the documents to the file gateway and set up a lifecycle policy to move the data into Glacier for data archival.
The option that says: Launch a new tape gateway that connects to your on-premises data center using AWS Storage Gateway. Upload the documents to the tape gateway and set up a lifecycle policy to move the data into Glacier for archival is incorrect because although tape gateways provide cost-effective and durable archive backup data in Amazon Glacier, it does not meet the criteria of being retrievable immediately within minutes. It also doesn't maintain a local cache that provides low latency access to the recently accessed data and reduce data egress charges. Thus, it is still better to set up a file gateway instead.
The option that says: Establish a Direct Connect connection to integrate your on-premises network to your VPC. Upload the documents on Amazon EBS Volumes and use a lifecycle policy to automatically move the EBS snapshots to an S3 bucket, and then later to Glacier for archival is incorrect because EBS Volumes are not as durable compared with S3 and it would be more cost-efficient if you directly store the documents to an S3 bucket. An alternative solution is to use AWS Direct Connect with AWS Storage Gateway to create a connection for high-throughput workload needs, providing a dedicated network connection between your on-premises file gateway and AWS. But this solution is using EBS, hence, this option is still wrong.
The option that says: Use AWS Snowmobile to migrate all of the files from the on-premises network.
Upload the documents to an S3 bucket and set up a lifecycle policy to move the data into Glacier for archival is incorrect because Snowmobile is mainly used to migrate the entire data of an on-premises data center to AWS. This is not a suitable approach as the company still has a hybrid cloud architecture which means that they will still use their on-premises data center along with their AWS cloud infrastructure.
References: https://docs.aws.amazon.com/AmazonS3/latest/dev/object-lifecycle-mgmt.html
https://docs.aws.amazon.com/storagegateway/latest/userguide/StorageGatewayConcepts.html Check out this Amazon S3 Cheat Sheet:
https://tutorialsdojo.com/amazon-s3/
Tutorials Dojo's AWS Certified Solutions Architect Associate Exam Study Guide:
https://tutorialsdojo.com/aws-certified-solutions-architect-associate-saa-c02/

 

NEW QUESTION 29
A startup plans to develop a multiplayer game that uses UDP as the protocol for communication between clients and game servers. The data of the users will be stored in a key-value store. As the Solutions Architect, you need to implement a solution that will distribute the traffic across a number of servers.
Which of the following could help you achieve this requirement?

A. Distribute the traffic using Network Load Balancer and store the data in Amazon Aurora.B. Distribute the traffic using Network Load Balancer and store the data in Amazon DynamoDB.C. Distribute the traffic using Application Load Balancer and store the data in Amazon DynamoDB.D. Distribute the traffic using Application Load Balancer and store the data in Amazon RDS.

Answer: B

Explanation:
A Network Load Balancer functions at the fourth layer of the Open Systems Interconnection (OSI) model.
It can handle millions of requests per second. After the load balancer receives a connection request, it selects a target from the target group for the default rule. For UDP traffic, the load balancer selects a target using a flow hash algorithm based on the protocol, source IP address, source port, destination IP address, and destination port. A UDP flow has the same source and destination, so it is consistently routed to a single target throughout its lifetime. Different UDP flows have different source IP addresses and ports, so they can be routed to different targets.



In this scenario, a startup plans to create a multiplayer game that uses UDP as the protocol for communications. Since UDP is a Layer 4 traffic, we can limit the option that uses Network Load Balancer. The data of the users will be stored in a key-value store. This means that we should select Amazon DynamoDB since it supports both document and key-value store models.
Hence, the correct answer is: Distribute the traffic using Network Load Balancer and store the data in Amazon DynamoDB.
The option that says: Distribute the traffic using Application Load Balancer and store the data in Amazon DynamoDB is incorrect because UDP is not supported in Application Load Balancer. Remember that UDP is a Layer 4 traffic. Therefore, you should use a Network Load Balancer.
The option that says: Distribute the traffic using Network Load Balancer and store the data in Amazon Aurora is incorrect because Amazon Aurora is a relational database service. Instead of Aurora, you should use Amazon DynamoDB.
The option that says: Distribute the traffic using Application Load Balancer and store the data in Amazon RDS is incorrect because Application Load Balancer only supports application traffic (Layer 7). Also, Amazon RDS is not suitable as a key-value store. You should use DynamoDB since it supports both document and key-value store models.
References:
https://aws.amazon.com/blogs/aws/new-udp-load-balancing-for-network-load-balancer/
https://docs.aws.amazon.com/elasticloadbalancing/latest/network/introduction.html Check out this AWS Elastic Load Balancing Cheat Sheet:
https://tutorialsdojo.com/aws-elastic-load-balancing-elb/

 

NEW QUESTION 30
An organization needs a persistent block storage volume that will be used for mission-critical workloads. The backup data will be stored in an object storage service and after 30 days, the data will be stored in a data archiving storage service.
What should you do to meet the above requirement?

A. Attach an instance store volume in your EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 One Zone-IA.B. Attach an EBS volume in your EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 One Zone-IA.C. Attach an instance store volume in your existing EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 Glacier.D. Attach an EBS volume in your EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 Glacier.

Answer: D

Explanation:
Amazon Elastic Block Store (EBS) is an easy-to-use, high-performance block storage service designed for use with Amazon Elastic Compute Cloud (EC2) for both throughput and transaction-intensive workloads at any scale. A broad range of workloads, such as relational and non-relational databases, enterprise applications, containerized applications, big data analytics engines, file systems, and media workflows are widely deployed on Amazon EBS.
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. In an S3 Lifecycle configuration, you can define rules to transition objects from one storage class to another to save on storage costs. Amazon S3 supports a waterfall model for transitioning between storage classes, as shown in the diagram below:

In this scenario, three services are required to implement this solution. The mission-critical workloads mean that you need to have a persistent block storage volume and the designed service for this is Amazon EBS volumes. The second workload needs to have an object storage service, such as Amazon S3, to store your backup data. Amazon S3 enables you to configure the lifecycle policy from S3 Standard to different storage classes. For the last one, it needs archive storage such as Amazon S3 Glacier.
Hence, the correct answer in this scenario is: Attach an EBS volume in your EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 Glacier.
The option that says: Attach an EBS volume in your EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 One Zone-IA is incorrect because this lifecycle policy will transition your objects into an infrequently accessed storage class and not a storage class for data archiving.
The option that says: Attach an instance store volume in your existing EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 Glacier is incorrect because an Instance Store volume is simply a temporary block-level storage for EC2 instances.
Also, you can't attach instance store volumes to an instance after you've launched it. You can specify the instance store volumes for your instance only when you launch it.
The option that says: Attach an instance store volume in your EC2 instance. Use Amazon S3 to store your backup data and configure a lifecycle policy to transition your objects to Amazon S3 One Zone-IA is incorrect. Just like the previous option, the use of instance store volume is not suitable for mission-critical workloads because the data can be lost if the underlying disk drive fails, the instance stops, or if the instance is terminated. In addition, Amazon S3 Glacier is a more suitable option for data archival instead of Amazon S3 One Zone-IA.
References:
https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AmazonEBS.html
https://aws.amazon.com/s3/storage-classes/ Check out this Amazon S3 Cheat Sheet:
https://tutorialsdojo.com/amazon-s3/
Tutorials Dojo's AWS Storage Services Cheat Sheets:
https://tutorialsdojo.com/aws-cheat-sheets-storage-services/

 

NEW QUESTION 31
A company hosts a data lake on AWS. The data lake consists of data in Amazon S3 and Amazon RDS for PostgreSQL. The company needs a reporting solution that provides data visualization and includes all the data sources within the data lake. Only the company's management team should have full access to all the visualizations. The rest of the company should have only limited access.
Which solution will meet these requirements?

A. Create an analysis in Amazon QuickSight. Connect all the data sources and create new datasets. Publish dashboards to visualize the data. Share the dashboards with the appropriate IAM roles.B. Create an AWS Glue table and crawler for the data in Amazon S3. Create an AWS Glue extract, transform, and load (ETL) job to produce reports. Publish the reports to Amazon S3. Use S3 bucket policies to limit access to the reports.C. Create an AWS Glue table and crawler for the data in Amazon S3. Use Amazon Athena Federated Query to access data within Amazon RDS for PoslgreSQL. Generate reports by using Amazon Athena. Publish the reports to Amazon S3. Use S3 bucket policies to limit access to the reports.D. Create an analysis in Amazon OuickSighl. Connect all the data sources and create new datasets. Publish dashboards to visualize the data. Share the dashboards with the appropriate users and groups.

Answer: A

 

NEW QUESTION 32
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